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112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West
OBJECTIVES/GOALS: Understanding how SARS-CoV-2 is evolving as well as spreading within and between communities is vital for the design of rational, evidence-based control measures. Continuous genomic surveillance is imperative to identify and track variants and can be paired with clinical data, to i...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209265/ http://dx.doi.org/10.1017/cts.2022.32 |
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author | Domman, Daryl Morley, Valerie Schwalm, Kurt Young, Jesse Griego, Anastacia Siebert, Margaret Edwards, Michael Goldberg, Emma Dinwiddie, Darrell |
author_facet | Domman, Daryl Morley, Valerie Schwalm, Kurt Young, Jesse Griego, Anastacia Siebert, Margaret Edwards, Michael Goldberg, Emma Dinwiddie, Darrell |
author_sort | Domman, Daryl |
collection | PubMed |
description | OBJECTIVES/GOALS: Understanding how SARS-CoV-2 is evolving as well as spreading within and between communities is vital for the design of rational, evidence-based control measures. Continuous genomic surveillance is imperative to identify and track variants and can be paired with clinical data, to identify associations with severity or vaccine breakthroughs. METHODS/STUDY POPULATION: In June of 2021, we established UNM as a CDC-funded hub for genomic surveillance of SARS-CoV-2 for New Mexico and 3 other Rocky Mountain region states (Wyoming, Idaho, Montana). Through our Rocky Mountain COVID Consortium (RMCC), we have sequenced over 6,000 genomes of SARS-CoV-2 from RMCC partners. For New Mexico we integrate county and zip code data to provide more granular insights into how SARS-CoV-2, and particular variants, are transmitting within the state. We also pair this data with vaccine breakthrough cases identified by the NMDOH, as well as with clinical outcome data. RESULTS/ANTICIPATED RESULTS: We sequenced over 6,000 SARS-CoV-2 genomes from New Mexico (n=3091), Idaho (n=1538), Arkansas (n=1101), Wyoming (n=251), and Montana (n=33). We used this data to infer the transmission dynamics, identify variants, and map the spread of the virus. We identified a novel local variant that spread across New Mexico in early 2021, but was quickly replaced by the Alpha variant. In all RMCC states, the Delta variant overtook Alpha and has become nearly the only variant currently circulating in these states. We identified sequenced isolates from vaccine breakthrough cases in NM and demonstrate their role in onward transmission. We can identify shifts at a county or zip-code level in circulating lineages which may correspond to clinical outcomes or fluctuating case counts. DISCUSSION/SIGNIFICANCE: This integrated genomic data can be used by policy and decision makers within the New Mexico Department of Health and our RMCC partners to guide their public health response to the COVID-19 pandemic. |
format | Online Article Text |
id | pubmed-9209265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92092652022-07-01 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West Domman, Daryl Morley, Valerie Schwalm, Kurt Young, Jesse Griego, Anastacia Siebert, Margaret Edwards, Michael Goldberg, Emma Dinwiddie, Darrell J Clin Transl Sci Community Engagement OBJECTIVES/GOALS: Understanding how SARS-CoV-2 is evolving as well as spreading within and between communities is vital for the design of rational, evidence-based control measures. Continuous genomic surveillance is imperative to identify and track variants and can be paired with clinical data, to identify associations with severity or vaccine breakthroughs. METHODS/STUDY POPULATION: In June of 2021, we established UNM as a CDC-funded hub for genomic surveillance of SARS-CoV-2 for New Mexico and 3 other Rocky Mountain region states (Wyoming, Idaho, Montana). Through our Rocky Mountain COVID Consortium (RMCC), we have sequenced over 6,000 genomes of SARS-CoV-2 from RMCC partners. For New Mexico we integrate county and zip code data to provide more granular insights into how SARS-CoV-2, and particular variants, are transmitting within the state. We also pair this data with vaccine breakthrough cases identified by the NMDOH, as well as with clinical outcome data. RESULTS/ANTICIPATED RESULTS: We sequenced over 6,000 SARS-CoV-2 genomes from New Mexico (n=3091), Idaho (n=1538), Arkansas (n=1101), Wyoming (n=251), and Montana (n=33). We used this data to infer the transmission dynamics, identify variants, and map the spread of the virus. We identified a novel local variant that spread across New Mexico in early 2021, but was quickly replaced by the Alpha variant. In all RMCC states, the Delta variant overtook Alpha and has become nearly the only variant currently circulating in these states. We identified sequenced isolates from vaccine breakthrough cases in NM and demonstrate their role in onward transmission. We can identify shifts at a county or zip-code level in circulating lineages which may correspond to clinical outcomes or fluctuating case counts. DISCUSSION/SIGNIFICANCE: This integrated genomic data can be used by policy and decision makers within the New Mexico Department of Health and our RMCC partners to guide their public health response to the COVID-19 pandemic. Cambridge University Press 2022-04-19 /pmc/articles/PMC9209265/ http://dx.doi.org/10.1017/cts.2022.32 Text en © The Association for Clinical and Translational Science 2022 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. |
spellingShingle | Community Engagement Domman, Daryl Morley, Valerie Schwalm, Kurt Young, Jesse Griego, Anastacia Siebert, Margaret Edwards, Michael Goldberg, Emma Dinwiddie, Darrell 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West |
title | 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West |
title_full | 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West |
title_fullStr | 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West |
title_full_unstemmed | 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West |
title_short | 112 Genomic surveillance for SARS-CoV-2 for New Mexico and the Mountain West |
title_sort | 112 genomic surveillance for sars-cov-2 for new mexico and the mountain west |
topic | Community Engagement |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209265/ http://dx.doi.org/10.1017/cts.2022.32 |
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